Use of Deep Learning in Modern Recommendation System: A Summary of Recent Works

TL;DR

This paper reviews recent advances in deep learning applications within recommendation systems, highlighting different system types, domain impacts, and future research directions, emphasizing deep learning's role in improving recommendation quality.

Contribution

It provides a comprehensive summary of recent deep learning techniques in recommendation systems, organized into collaborative, content-based, and hybrid approaches, and discusses their impact across various domains.

Findings

Deep learning enhances recommendation accuracy over traditional methods.

Hybrid systems effectively combine collaborative and content-based approaches.

Deep learning's impact varies across application domains.

Abstract

With the exponential increase in the amount of digital information over the internet, online shops, online music, video and image libraries, search engines and recommendation system have become the most convenient ways to find relevant information within a short time. In the recent times, deep learning's advances have gained significant attention in the field of speech recognition, image processing and natural language processing. Meanwhile, several recent studies have shown the utility of deep learning in the area of recommendation systems and information retrieval as well. In this short review, we cover the recent advances made in the field of recommendation using various variants of deep learning technology. We organize the review in three parts: Collaborative system, Content based system and Hybrid system. The review also discusses the contribution of deep learning integrated recommendation systems into several application domains. The review concludes by discussion of the impact of deep learning in recommendation system in various domain and whether deep learning has shown any significant improvement over the conventional systems for recommendation. Finally, we also provide future directions of research which are possible based on the current state of use of deep learning in recommendation systems.